This study explores the application of the co-design approach in participatory planning for the development of Kambo Tourism Village, located at the intersection of urban and rural areas in Indonesia. By combining the Delphi Consensus Method and Analytic Hierarchy Process (AHP), the study successfully identified and prioritized key aspects in the planning process, with a primary focus on local community participation. The results indicate that the co-design approach is effective in creating a masterplan that not only aligns with the needs and aspirations of the community but also supports the sustainability and inclusiveness of tourism village development. AHP results reveal that local community participation was assigned the highest priority with a weight of 0.35, followed by stakeholder collaboration with a weight of 0.27. Community participation not only contributed to the creation of a well-structured tourism village masterplan but also enhanced human resource quality and strengthened stakeholder collaboration. The impact of this participatory planning process includes increased national recognition for Kambo Village, the village’s success in receiving awards, and local economic growth. Moreover, the study identified a gap between the calculated and expected weights in the AHP process, highlighting the complexity of aligning diverse stakeholder perspectives. These findings offer both practical and theoretical contributions and open opportunities for further research to address the challenges of participatory planning in the context of tourism villages.

Due to the incapacity of families in Sub-Saharan African nations to satisfy basic necessities for home maintenance, this study is required to enable policy shifts in the area of consumption tax. The study looks at the impact of consumption taxes on the purchasing power of families in Sub-Saharan Africa, with an emphasis on Nigeria and Kenya. The datasets used for this inquiry range from 1994 to 2022. Among the factors are purchasing power parity (PPP), value added tax (VAT), and exchange rate. We obtained the statistics from the World Bank, the Central Banks of Nigeria and Kenya, the Federal Inland Revenue Service, and the Organization for Economic Co-operation and Development (OECD). The study used the autoregressive distributed lag (ARDL) model established by Pesaran et al. (2001). The findings reveal that the inclusion of VAT on the prices of products and services significantly harms households throughout Nigeria compared to those in Kenya. VAT has a significant negative impact on consumer purchasing power in Nigeria but has an immaterial negative impact on household spending capacity in Kenya. The influence of the currency rate is positive and beneficial in Nigeria, whereas it is negative but intangible in Kenya. Due to economic disparity, the report suggests policy reforms in favour of families. It is also suggested that the government develop additional work possibilities, diversify the economy, and give subsidies for basic housing necessities.

The present study focuses on improving Cognitive Radio Networks (CRNs) based on applying machine learning to spectrum sensing in remote learning scenarios. Remote education requires connection dependability and continuity that can be affected by the scarcity of the amount of usable spectrum and suboptimal spectrum usage. The solution for the proposed problem utilizes deep learning approaches, namely CNN and LSTM networks, to enhance the spectrum detection probability (92% detection accuracy) and consequently reduce the number of false alarms (5% false alarm rate) to maximize spectrum utilization efficiency. By developing the cooperative spectrum sensing where many users share their data, the system makes detection more reliable and energy-saving (achieving 92% energy efficiency) which is crucial for sustaining stable connections in educational scenarios. This approach addresses critical challenges in remote education by ensuring scalability across diverse network conditions and maintaining performance on resource-constrained devices like tablets and IoT sensors. Combining CRNs with new technologies like IoT and 5G improves their capabilities and allows these networks to meet the constantly changing loads of distant educational systems. This approach presents another prospect to spectrum management dilemmas in that education delivery needs are met optimally from any STI irrespective of the availability of resources in the locale. The results show that together with machine learning, CRNs can be considered a viable path to improving the networks' performance in the context of remote learning and advancing the future of education in the digital environment. This work also focuses on how machine learning has enabled the enhancement of CRNs for education and provides robust solutions that can meet the increasing needs of online learning.

The digitalization of the construction industry is deemed a crucial element in Construction 4.0’s vision, attainable through the implementation of digital twinning. It is perceived as a virtual strategy to surmount the constraints linked with traditional construction projects, thereby augmenting their productivity and effectiveness. However, the neglect to investigate the causal relationship between implementation and construction project management performance has resulted from a lack of understanding and awareness regarding the consequences of digital twinning implementation, combined with a shortage of expertise among construction professionals. Consequently, this paper extensively explores the relationship between digital twinning implementation and construction project management performance. The Innovation Diffusion Theory (IDT) is employed to investigate this relationship, utilizing a quantitative research approach through document analysis and questionnaire surveys. Additionally, partial least squares structural equation modeling (PLS-SEM) with SmartPLS software is employed to deduce the relationship. The results underscore that digital twinning implementation significantly improves construction project management performance. Despite recognizing various challenges in digital twinning implementation, when regarded as moderating factors, these challenges do not significantly impact the established causal relationship. Therefore, this investigation aligns with the national push toward the digitalization of the construction sector, highlighting the positive impacts of digital twinning implementation on construction project management performance. Moreover, this study details the impacts of implementing digital twinning from the construction industry’s perspective, including positive and negative impacts. Afterwards, this paper addresses the existing research gap, providing a more precise understanding and awareness among construction industry participants, particularly in developing nations.

This study aims to discover the relationship between growth sales, capital structure, and corporate governance on financial performance of energy and basic material sector public companies in Indonesia. Financial performance is observed from 2 aspects: market performance (Tobin's Q) and profitability performance (ROA). The population in this study is firms in the energy and basic material sector on Indonesia Stock Exchange. The total population is 248 firms. 39 firms were selected as samples. The data is obtained from the annual report which starts from the period 2018 to 2022. A total of the population was determined as samples by purposive sampling method. Data analysis using panel data regression. The result shows: 1) Growth Sales have a significant influence on market performance; however, it does not have a significant effect on profitability performance. 2) Capital Structure significantly influences market and profitability performance 3) Corporate governance significantly influences market and profitability performance. Suggestions for companies that must strive to increase sales, maintain good corporate governance and pay attention to the company's capital structure in a balanced manner.